scholarly journals An Adaptive Model Predictive Voltage Control for LC-Filtered Voltage Source Inverters

2021 ◽  
Vol 11 (2) ◽  
pp. 704
Author(s):  
Hosein Gholami-Khesht ◽  
Pooya Davari ◽  
Frede Blaabjerg
Keyword(s):  
Control System ◽  
System Performance ◽  
State Space Model ◽  
Adaptive Observer ◽  
Voltage Source ◽  
Adaptive Model ◽  
Space Model ◽  
System Uncertainties ◽  
Augmented State ◽  
Load Conditions

The three-phase inductor and capacitor filter (LC)-filtered voltage source inverter (VSI) is subjected to uncertain and time-variant parameters and disturbances, e.g., due to aging, thermal effects, and load changes. These uncertainties and disturbances have a considerable impact on the performance of a VSI’s control system. It can degrade system performance or even cause system instability. Therefore, considering the effects of all system uncertainties and disturbances in the control system design is necessary. In this respect and to tackle this issue, this paper proposes an adaptive model predictive control (MPC), which consists of three main parts: an MPC, an augmented state-space model, and an adaptive observer. The augmented state-space model considers all system uncertainties and disturbances and lumps them into two disturbance inputs. The proposed adaptive observer determines the lumped disturbance functions, enabling the control system to keep the nominal system performance under different load conditions and parameters uncertainty. Moreover, it provides load-current-sensorless operation of MPC, which reduces the size and cost, and simultaneously improves the system reliability. Finally, MPC selects the proper converter voltage vector that minimizes the tracking errors based on the augmented model and outputs of the adaptive observer. Simulations and experiments on a 5 kW VSI examine the performance of the proposed adaptive MPC under different load conditions and parameter uncertainties and compare them with the conventional MPC.

scholarly journals Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Gergely Takács ◽  
Tomáš Polóni ◽  
Boris Rohal’-Ilkiv
Keyword(s):  
Control System ◽  
Vibration Control ◽  
State Space ◽  
Real Time ◽  
Cantilever Beam ◽  
State Space Model ◽  
Model Parameters ◽  
Extended Kalman Filtering ◽  
Space Model ◽  
Continuous State

This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

Analysis of a Hydrofoil Craft with a Suspension System

2020 ◽  
Author(s):  
Michel Touw ◽  
Jacob Lotz ◽  
Ido Akkerman
Keyword(s):  
Experimental Data ◽  
Control System ◽  
State Space ◽  
State Space Model ◽  
Suspension System ◽  
Future Research ◽  
Passive System ◽  
Height Control ◽  
Space Model ◽  
Front Wing

In this paper we investigate the efficacy of augmenting, or replacing, an active height control system for a submerged hydrofoil with a passive system based on springs and dampers. A state-space model for submerged hydrofoils is formulated and extended to allow for a suspension at the front wing, aft wing or both wings. The model is partially verified by obtaining results in the fixed-wing limit and comparing these with experimental data from the MARIN Foiling Future Demonstrator. In the current study we limit ourselves to translational springs, only allowing suspension motion in the heave direction. This results in unfavorable behavior: either the motions increased or the system becomes unstable. It is therefore recommended for future research to try rotational springs.

Modeling and Simulation of Controlled Manipulation by AFM Nano Robot

2011 ◽  
Vol 110-116 ◽  
pp. 3688-3695 ◽  
Author(s):  
Ali Kafash Hoshiar ◽  
Mohamad Reza Khalili ◽  
Mahmood Hashemi Nejad ◽  
Hafez Raeisi Fard
Keyword(s):  
Finite Element ◽  
Control System ◽  
Process Control ◽  
Control Algorithm ◽  
State Space Model ◽  
Force Transducer ◽  
Process Control System ◽  
Space Model ◽  
Element Simulation ◽  
Recent Developments

In this article a model to describe relation between AFM cantilever’s deformation and force (as a force transducer) is developed. Furthermore a state space model is used to find suitable feedback control. A model which relates force and deformation is described. To verify a Finite element simulation is applied and a control algorithm for manipulation purpose is found. Moreover based on nature of the process control system is designed. Due to recent developments in AFM nanorobot applications in biotechnology and manufacturing nanostructures, understanding of cantilever’s response and process control have received great importance.

The Design of Space Scanning Mirror Control System Based on Optimal Tracking Controller

2012 ◽  
Vol 546-547 ◽  
pp. 790-794
Author(s):  
Wen Bo Sui ◽  
Ke Fei Song ◽  
Pei Jie Zhang
Keyword(s):  
Control System ◽  
State Space ◽  
Pid Controller ◽  
Simulation Experiment ◽  
State Space Model ◽  
System State ◽  
Scanning Mirror ◽  
Optimal Tracking ◽  
Space Model ◽  
Tracking Controller

Control system of space scanning mirror has high requirement of scanning accuracy. The use of optimal tracking controller, instead of traditional PID controller, can effectively improve the scanning accuracy of space scanning mirror control system. State space model of the control system is established; the control system based on optimal tracking controller is designed; simulation experiment of the control system based on optimal tracking controller is carried out. The simulation result, in comparison with the system based on a PID controller, shows that the scanning mirror control system using optimal tracking controller instead of PID controller has higher scanning accuracy and faster response.

Estimation of Forcing Function, Mistuning and Modal Damping in a Bladed Rotor

2019 ◽  
Author(s):  
Arjun Singh Chauhan ◽  
Alok Sinha
Keyword(s):  
Kalman Filter ◽  
State Space ◽  
Unscented Kalman Filter ◽  
State Space Model ◽  
Space Model ◽  
Vibration Data ◽  
Forcing Function ◽  
Modal Damping ◽  
Bladed Rotor ◽  
Augmented State

Abstract This paper deals with the estimation of forcing function, modal damping and mistuned modal stiffnesses in a bladed rotor. Previous research on parameter estimation in a mistuned bladed rotor relies on the knowledge of the forcing function as well as the vibration data. This paper presents two novel approaches. The first approach relies on knowledge of both the forcing and vibration data. The parameters are treated as states of the system and an augmented state space model is created. Unscented Kalman Filter is then used on the steady state data to estimate the parameters. The second approach eliminates the dependence on forcing data. Both the forcing and parameters are now treated as states of the system to construct an augmented state space model. Unscented Kalman Filter is then used on transient vibration data for estimation. Numerical results are presented for a simple model of a mistuned bladed rotor which considers a single mode of vibration per blade.

Research on Control System of Pump and Valve Parallel Connection

2010 ◽  
Vol 44-47 ◽  
pp. 1751-1757 ◽  
Author(s):  
Jing Luo ◽  
Chun Geng Sun ◽  
Peng Zhang ◽  
Sen Liu ◽  
Song Tao Wu
Keyword(s):  
Control System ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Parallel Connection ◽  
Space Model ◽  
Valve System ◽  
Simulation Results ◽  
Valve Control

This paper introduces the composition of pump and valve control system of parallel connection and the output flux of pump and valve is distributed optimally. Then, establish the state-space model of pump and valve system, the system is simulated by Simlink and AMESim software, the simulation results obtained.

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